The monitoring or evaluation of film or video content is an area of growing interest, both for broadcasters and for content owner or content management organizations.
In particular, it is desirable for broadcast organizations to be able to monitor the audio-visual content being broadcast to identify, and therefore quickly respond to, problems or errors in the broadcast chain, for example a loss of picture. This may be caused by a number of factors, for example: failure of a radio frequency link; play-out of video information from a store that has not been initialized properly; play out of blank D5 tape; or other fault conditions as will be apparent to a skilled person.
Typically, previously this has been achieved by a person visually monitoring the program output, or more generally monitoring a number of program outputs, and visually identifying errors in the program output. Clearly, this is personnel-intensive and it is desirable to provide automated or semi-automated monitoring and error protection.
One approach to this problem is to estimate the noise floor power level. An image can then be flagged as a “non-picture” image if the noise floor power level exceeds a threshold.
A problem with this approach is that the noise floor power level derived mathematically from an image does not necessarily correlate accurately with the perceived level of noise in the image. Thus this technique may result in inaccurate identification of images as non-picture images. Another disadvantage arises from the necessity to use a frame store to achieve temporal averaging when implementing in hardware, which may be difficult in resource-limited implementations.